PMHT for tracking with timing uncertainty

Abstract

This paper considers the problem of tracking a target using measurements where the temporal information is noisy or unreliable. The measurements are modelled as being received with a stochastic time delay. By treating the true measurement time as missing data and using Expectation-Maximisation, a modified version of the Probabilistic Multi Hypothesis Tracker (PMHT) is derived for the uncertain timing problem. This modified PMHT thus associates each measurement to the targets and to time instants. The method is demonstrated using simulations and the improvement quantified over using the standard PMHT in ignorance of the noisy time data.